Combination of two methodologies, artificial neural network and linear interpolation, to gap-fill daily nitrous oxide flux measurements-Reference-Cited by-同舟云学术

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Combination of two methodologies, artificial neural network and linear interpolation, to gap-fill daily nitrous oxide flux measurements

Published:2020-09 Issue: Volume:291 Page:108037
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Bigaignon Laurent,Fieuzal Rémy,Delon Claire^ORCID,Tallec Tiphaine^ORCID

Funder

Institut National des Sciences de l'Univers, Centre National de la Recherche Scientifique

Université Toulouse III - Paul Sabatier

Publisher

Elsevier BV

Subject

Atmospheric Science,Agronomy and Crop Science,Global and Planetary Change,Forestry

Reference41 articles.

1. Carbon balance of a three crop succession over two cropland sites in South West France;Béziat;Agric. Forest Meteorol.,2009

2. Neural Networks for Pattern Recognition;Bishop,1995

3. The contribution of manure and fertilizer nitrogen to atmospheric nitrous oxide since 1860;Davidson;Nat. Geosci.,2009

4. Testing the applicability of neural networks as a gap-filling method using CH4 flux data from high latitude wetlands;Dengel;Biogeosciences,2013

5. Soil NO emissions modelling using artificial neural network;Delon;Tellus B,2007

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